Explosion protection with AI
An engineering firm achieves ten times more than before.
The engineering firm achieves ten times more than before, while the technical review remains with its experts.
- more output at the engineering firm
- 10×
- more output at the engineering firm
Overview
01 · Problem
Expertise and documentation depended on a few specialists.
02 · Approach
An internal AI knowledge and process solution prepared enquiries and documents.
03 · Result
The firm can handle ten times more work; approval and responsibility remain with the specialists.
Before / after
What changed in the business.
Engineering firms & experts
Using internal AI in an engineering firm
Starting point
In a specialised engineering firm for explosion protection, qualified working time was the bottleneck. Work on standards, hazard assessments and result documents nevertheless requires expert control.
How does internal AI support specialist processes in explosion protection?
During the project, an internal AI knowledge solution and a configurator for preparing customer enquiries were built. Preparatory work and documents that can be standardised are supported.
Technical review and approval remain with the experts. This allows the firm to handle ten times more work than before.
At a glance
Levers and services.
- Services
- StrategyConceptImplementation
- Type of solution
- AI & company knowledge
- Industry
- Engineering firms & experts
Result
Result and assessment.
- more output at the engineering firm
- 10×
- more output at the engineering firm
The engineering firm achieves ten times more than before, while the technical review remains with its experts.
What entrepreneurs can take from this
Expert knowledge scales when preparatory work and documentation are prepared in a standardised way and the decision stays with a person.
A mechanism, not a promise of results: the effect depends on your starting process.
What this means for you
Building blocks from this case.
This project gave rise to use cases that we now deploy in other companies, adapted to their processes.
Frequently asked questions
Questions about this case.
Your question is not here? In the initial conversation we take 30 minutes for your specific topic.
No. The AI prepares enquiries, research and documents. Review, approval and professional responsibility remain with the firm's experts.
The engineering firm achieves ten times more than before, while the technical review remains with its experts.
The principle yes, the implementation never one to one. Expert knowledge scales when preparatory work and documentation are prepared in a standardised way and the decision stays with a person. In the initial conversation we check which part of it has the greatest leverage for you.
More case studies
Similar cases.
Several days
less administrative work per month
Travel & hotelsAI & knowledgeAI for gentle travel: Coordinating hundreds of tour leaders, guides and partners while on the move.
What changed? Coordination became possible on the move and saved several days of administrative work per month.
View case
One workflow
from job description to onboarding
Utilities & suppliersAI & knowledgeHR management for municipal utilities: Automated workflow system from the job description through application and selection to onboarding.
What changed? Reminders and status messages reduced the risk of overlooking applications and replies.
View case
More overnight stays
in all hotels of the group
Travel & hotelsAI & knowledgeMore overnight stays in all hotels: Overnight stays become short breaks. AI adjusts prices live according to demand and season.
What changed? The number of overnight stays rose in all hotels.
View case
Does your growth depend on a few experts?
In the free initial conversation we look at your process, show a comparable project and assess where the greatest lever lies.
Free · 20 minutes · online